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Product Talk · Teresa TorresOct 22, 2025

AI Changes Everything (And Nothing At All)

Oct 22, 2025 · 12 min

Teresa Torres argues that generative AI changes many product-management practices (prompt engineering, context engineering, orchestration, and evals) but that core fundamentals still determine whether a product…

Lenny’s Podcast95 min

How to measure AI developer productivity in 2025

Nicole Forsgren · Oct 19, 2025
Key learnings
  • Before measuring anything, get crisp on the problem or goal, since teams often interpret vague mandates like 'improve developer…
  • Shipping smaller changes more often tends to improve both speed and stability together, because small batches have smaller blast…
  • DORA's four metrics (deployment frequency, lead time, time to restore, change fail rate) give a benchmark-style view of where you…
Lenny’s Newsletter♥ 839

Everyone should be using Claude Code more

Oct 14, 2025 · 20 min
Subscriber post — summary only

Lenny Rachitsky argues that non-technical people should use Claude Code, which he frames as a local-feeling AI agent that can act on files and tools on a computer. The post walks through installation steps, shows five…

HEY World · Jason FriedOct 13, 2025

The next product

Oct 13, 2025

Jason Fried argues that a new product does not need to be revolutionary or disruptive to succeed. He describes how whole product categories can drift toward ever-greater complexity, with competitors one-upping each…

Medium · Hiten ShahOct 12, 2025

When Everyone Builds in Public

Oct 12, 2025

Hiten Shah argues that building in public began as a risky, honest practice where founders shared unfinished thinking to find like-minded people and sharpen their own conviction. As audiences grew and tools for…

Lenny’s Podcast118 min

Inside Google's AI turnaround: The rise of AI Mode, strategy behind AI Overviews, and their vision for AI-powered search

Robby Stein · Oct 10, 2025
Key learnings
  • Search demand is expanding rather than dying: AI lets people ask more and harder questions, so growth comes from new query types…
  • Build a product from a real user problem and stay dissatisfied with the status quo; keep making it better until it tips into…
  • Use a J-curve retention analysis (day 7, 30, 90) to tell whether a product is flattening into real usage or steadily losing users.
Lenny’s Podcast110 min

First interview with Scale AI’s CEO: $14B Meta deal, what’s working in enterprise AI, and what frontier labs are building next

Jason Droege · Oct 9, 2025
Key learnings
  • Model improvement now relies heavily on experts (80% of Scale's expert network holds a bachelor's or higher) defining what good…
  • Enterprise AI pilots that reach 60-70% accuracy feel close, but robust automation of important processes often takes 6-12 months…
  • Validate a new business by checking whether it can sustain high gross margins and whether competitors can match the economics in…
HEY World · Jason FriedOct 7, 2025

When design drives behavior

Oct 7, 2025

Jason Fried argues that the most interesting design is the kind that changes how people behave, not just how something looks or works. He uses the power reserve indicator on the A. Lange & Söhne Lange 1 watch as an…

Lenny’s Podcast115 min

How to find hidden growth opportunities in your product

Albert Cheng · Oct 5, 2025
Key learnings
  • Alternate between exploring for new insights and exploiting proven wins; when experiments stop reaching significance, return to…
  • Share experiment learnings across the company so adjacent teams can apply the same human-psychology insight to their own parts of…
  • Make a free tier a taste of the full product's value rather than a stripped-down version; sampling paid suggestions to free users…
Lenny’s Podcast112 min

The secret to better AI prototypes: Why Tinder’s CPO starts with JSON, not design

Ravi Mehta · Sep 29, 2025
Key learnings
  • Startups win on latency, the speed from idea to validated result, not raw velocity; design tests so you can learn in days rather…
  • Early-stage companies lack the traffic for statistically significant experiments, so favor conviction built from enough data over…
  • Build an early-stage network of founders, angels, and builders early, since large-company connections often prefer staying in…
HEY World · Jason FriedSep 25, 2025

What to do with $2M?

Sep 25, 2025

Jason Fried responds to a young entrepreneur in his mid-20s who sold a business and now holds a couple million dollars in liquid cash, asking whether to invest it, start a new company, or do something else. Fried's…

Lenny’s Podcast131 min

Why AI evals are the hottest new skill for product builders

Hamel Husain & Shreya Shankar · Sep 25, 2025
Key learnings
  • Evals are systematic ways to measure and improve an AI application, essentially data analytics on LLM behavior, replacing…
  • Start with error analysis by manually reviewing around 100 sampled traces and writing short notes on the first upstream failure…
  • Product people with domain expertise should lead open coding; appoint one 'benevolent dictator' whose judgment you trust instead…
Lenny’s Podcast81 min

Why experts writing AI evals is creating the fastest-growing companies in history

Brendan Foody · Sep 18, 2025
Key learnings
  • Treat evals as the product requirement document for a model: if you cannot measure what success looks like for a task, you cannot…
  • Companies should build a systematic test of how AI automates their core value chain, since that measurement is the prerequisite…
  • Evals also serve as sales collateral, showing customers and researchers concretely which real-world capabilities a model or…
SVPG · Marty CaganSep 17, 2025

Forward Deployed Engineers

Sep 17, 2025 · 5 min

Marty Cagan argues that Forward Deployed Engineers (FDEs)—technical product creators who embed with customers to deeply understand their problems—are a powerful practice that applies well beyond the hard, high-stakes…